I think those boosts shown are reflecting the edit distance. What we can't see from this is that the Similarity class used in execution is using the same IDF for all terms. The other factors at play will be the term frequency in the doc, its length and any doc boost. I don't have access to the code right now but that is how I remember it working. There may be an option to turn term frequency off too.
On 27 Aug 2009, at 14:25, Berkes Adam <adam.ber...@intland.com> wrote: After searching for term "desy" which has lot of variants in our index a rewritten (sub)query will look like this: (text:dey^0.22828968 text:des^0.22828968 text:dest^1.1557184 text:desk^1.1557184 text:desi^1.1557184 text:desf^1.1557184 text:desc^1.1557184 text:deny^1.1557184 text:defy^1.1557184 text:desy^8.218443) but what I would like to achive to have all exact matches (even if rankings "validly" send it to the end of matches) on top (or highest possible) while let variants to follow them according to their relevancy. Maybe I understand wrongly but the edit distance is not a factor in that query type: index is search for terms with edit distance within a certain limit, eliminate IDF (with the factors above) and then create a coordinationless boolean query. I might play around (post modify) scoring for exact match subterm but I'm not sure that is a working solution. Best regards, Adam Despite making IDF a constant the edit distance should remain a factor in the rankings so I would have thought this would give you what you need. Can you supply a more detailed example? Either print the rewritten query or use the explain function Cheers Mark On 27 Aug 2009, at 13:22, Berkes Adam wrote: Hi, In our java project we uses a (slightly modifed) version of FuzzyLikeThis query which "For each source term the fuzzy variants are held in a BooleanQuery with no coord factor (because we are not looking for matches on multiple variants in any one doc). Additionally, a specialized TermQuery is used for variants and does not use that variant term's IDF because this would favour rarer terms eg misspellings. Instead, all variants use the same IDF ranking (the one for the source query term) and this is factored into the variant's boost. If the source query term does not exist in the index the average IDF of the variants is used." In most cases it performs well but if there is short query term with (as usual) big number of variants the exact matches will be stay spreaded among the others which is not so useful: it should be "sorted" like (or forcibly set more relevant) exact matches and variant matches according to relevancy. Is there any simple solution or already implemented contrib query class for this problem? Best regards, Adam Berkes, Intland Software --------------------------------------------------------------------- To unsubscribe, e-mail: java-dev-unsubscr...@lucene.apache.org For additional commands, e-mail: java-dev-h...@lucene.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: java-dev-unsubscr...@lucene.apache.org For additional commands, e-mail: java-dev-h...@lucene.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: java-dev-unsubscr...@lucene.apache.org For additional commands, e-mail: java-dev-h...@lucene.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: java-dev-unsubscr...@lucene.apache.org For additional commands, e-mail: java-dev-h...@lucene.apache.org
